In recent years, many methods for subband or wavelet compression of images have been proposed. One such method is the EBCOT algorithm as described in D. Taubman, “High performance scalable compression with EBCOT,” IEEE Transactions on Image Processing, 9(7), pp. 1158-1170 (July 2000). The emerging JPEG2000 image compression standard, as described in Information Technology—JPEG2000 Image Coding System, ISO/IEC International Standard 15444-1, ITU Recommendation T.800, is based on the EBCOT algorithm.
The EBCOT algorithm decomposes the image using a wavelet transform. The resulting subbands are further divided into smaller codeblocks. The codeblocks are quantized and entropy coded independently. The EBCOT algorithm uses two different methods to allocate bits to different codeblocks. In one method, the mean squared error (MSE), possibly weighted, is estimated assuming that the compressed bit-stream is truncated at each potential truncation point. Then, a truncation point is chosen for each codeblock after analyzing the rate-distortion trade-off. In another method, the MSE is adjusted by a factor that accounts for the visibility of quantization noise at a particular spatio-frequency location, based on the visual masking property of the human visual system (HVS).
The prior art mentioned above is limited to rate-distortion trade-offs in different spatio-frequency regions according to low-level visual characteristics. There is also a need to perform such trade-off based on the semantic meaning of the objects in an image. It is desirable to allocate more bits to regions of interest (ROIs) or foreground regions for relatively higher quality in such regions, while allocating fewer bits to the background regions. This maximizes the visual quality of regions that are likely to be important for the reconstructed image quality as perceived by the end-user. Conventionally, the ROI is specified using a binary mask as described in C. Christopoulos, J. Askelof and M. Larsson, “Efficient regions of interest encoding techniques in the upcoming JPEG2000 still image coding standard,” IEEE International Conference on Image Processing, September 2000, Vancouver, Canada. A drawback of using a binary ROI mask is that the result is extremely sensitive to the correctness and accuracy of the binary mask; and there is no known robust automatic method for generating an accurate binary mask.